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We investigate how users interact with the results page of a WWW search engine using eye-tracking. The goal is to gain insight into how users browse the presented abstracts and how they select links for further exploration. Such understanding is valuable for improved interface design, as well as for more accurate interpretations of implicit feedback (e.g. clickthrough) for machine learning. The following presents initial results, focusing on the amount of time spent viewing the presented abstracts, the total number of abstract viewed, as well as measures of how thoroughly searchers evaluate their results set.
@inproceedings{1009079, author = {Laura A. Granka and Thorsten Joachims and Geri Gay}, title = {Eye-tracking analysis of user behavior in WWW search}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {478--479}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009079}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
